Loading...
Searching...
No Matches
icp_nl.h
/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2010-2011, Willow Garage, Inc.
* Copyright (c) 2012-, Open Perception, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* $Id$
*
*/
#pragma once
// PCL includes
#include <pcl/registration/icp.h>
#include <pcl/registration/transformation_estimation_lm.h>
namespace pcl {
/** \brief @b IterativeClosestPointNonLinear is an ICP variant that uses
* Levenberg-Marquardt optimization backend. The resultant transformation is optimized
* as a quaternion.
*
* The algorithm has several termination criteria:
*
* <ol>
* <li>Number of iterations has reached the maximum user imposed number of iterations
* (via \ref setMaximumIterations)</li>
* <li>The epsilon (difference) between the previous transformation and the current
* estimated transformation is smaller than an user imposed value (via \ref
* setTransformationEpsilon)</li> <li>The sum of Euclidean squared errors is smaller
* than a user defined threshold (via \ref setEuclideanFitnessEpsilon)</li>
* </ol>
*
* \author Radu B. Rusu, Michael Dixon
* \ingroup registration
*/
template <typename PointSource, typename PointTarget, typename Scalar = float>
class IterativeClosestPointNonLinear
: public IterativeClosestPoint<PointSource, PointTarget, Scalar> {
using IterativeClosestPoint<PointSource, PointTarget, Scalar>::
min_number_correspondences_;
using IterativeClosestPoint<PointSource, PointTarget, Scalar>::reg_name_;
using IterativeClosestPoint<PointSource, PointTarget, Scalar>::
transformation_estimation_;
using IterativeClosestPoint<PointSource, PointTarget, Scalar>::computeTransformation;
public:
using Ptr =
shared_ptr<IterativeClosestPointNonLinear<PointSource, PointTarget, Scalar>>;
using ConstPtr = shared_ptr<
const IterativeClosestPointNonLinear<PointSource, PointTarget, Scalar>>;
using Matrix4 = typename Registration<PointSource, PointTarget, Scalar>::Matrix4;
/** \brief Empty constructor. */
IterativeClosestPointNonLinear()
{
min_number_correspondences_ = 4;
reg_name_ = "IterativeClosestPointNonLinear";
transformation_estimation_.reset(
new pcl::registration::
TransformationEstimationLM<PointSource, PointTarget, Scalar>);
}
};
} // namespace pcl
pcl::IterativeClosestPoint< PointSource, PointTarget, float >::IterativeClosestPoint
IterativeClosestPoint()
Definition icp.h:146
pcl::IterativeClosestPoint< PointSource, PointTarget, float >::computeTransformation
void computeTransformation(PointCloudSource &output, const Matrix4 &guess) override
Definition icp.hpp:115
pcl::IterativeClosestPointNonLinear::Matrix4
typename Registration< PointSource, PointTarget, Scalar >::Matrix4 Matrix4
Definition icp_nl.h:82
pcl::IterativeClosestPointNonLinear::Ptr
shared_ptr< IterativeClosestPointNonLinear< PointSource, PointTarget, Scalar > > Ptr
Definition icp_nl.h:77
pcl::IterativeClosestPointNonLinear::ConstPtr
shared_ptr< const IterativeClosestPointNonLinear< PointSource, PointTarget, Scalar > > ConstPtr
Definition icp_nl.h:79
pcl::IterativeClosestPointNonLinear::IterativeClosestPointNonLinear
IterativeClosestPointNonLinear()
Empty constructor.
Definition icp_nl.h:85
pcl::Registration< PointSource, PointTarget, float >::reg_name_
std::string reg_name_
Definition registration.h:548
pcl::Registration::Matrix4
Eigen::Matrix< Scalar, 4, 4 > Matrix4
Definition registration.h:59
pcl::Registration< PointSource, PointTarget, float >::transformation_estimation_
TransformationEstimationPtr transformation_estimation_
Definition registration.h:625
pcl::Registration< PointSource, PointTarget, float >::min_number_correspondences_
unsigned int min_number_correspondences_
Definition registration.h:618
pcl::registration
Definition convergence_criteria.h:46
pcl
Definition convolution.h:46